Systems and methods for detecting a medical emergency event

ABSTRACT

A computer-implemented method for detecting medical emergency events may include, via one or more processors, data sensors, and/or transceivers: (1) obtaining sensor data indicative of kinetic actions of a user; (2) analyzing the sensor data to associate the sensor data with a one or more kinetic actions of the user; (3) comparing the one or more kinetic actions of the user with a model of kinetic actions to determine whether the one or more kinetic actions correspond with the model of kinetic actions, with the model being indicative of a medical emergency event; and (4) upon determining that the one or more kinetic actions correspond with the model, contacting medical emergency responders to request medical emergency services for the user. As such, medical emergency events being experienced by a user can be detected, and medical emergency responders may be quickly contacted to provide essential emergency medical services to the individual.

CROSS-REFERENCE TO RELATED APPLICATIONS

The current patent application is a continuation of, and claims thebenefit of, U.S. patent application Ser. No. 15/961,320, filed Apr. 24,2018 and entitled “Systems and Methods for Detecting a Medical EmergencyEvent,” which claims priority benefit with regard to all common subjectmatter to U.S. Provisional Application Ser. No. 62/491,447, titled“MEDICAL EMERGENCY EVENT DETECTION WITH AUTOMATED EMERGENCY RESPONSE”,filed Apr. 28, 2017. The listed earlier-filed provisional application ishereby incorporated by reference in its entirety into the current patentapplication.

FIELD OF THE INVENTION

The present disclosure generally relates to computer-implementedmethods, systems, and electronic devices for collecting data related tokinetic actions of an individual and for determining the existence of amedical emergency event based upon such kinetic actions.

BACKGROUND

Individuals who experience medical emergency events may requireimmediate medical services and/or treatment but may be incapacitated andunable to request for such services. For example, an individual thatexperiences a cardiac event (e.g., a heart attack) may becomeunconscious and collapse to the ground. Unless emergency medicalresponders are notified within minutes of the onset of the medicalemergency event, the individual may have a low expectancy of surviving.Unfortunately, if the individual is alone, it is doubtful that emergencymedical responders will be notified in sufficient time because theindividual will likely be unconscious and/or otherwise incapacitated.Technology for determining the existence of a medical emergency event ispresently lacking outside of expensive medical equipment, which isprimarily used in hospitals or other medical facilities. Similarly,technology is also presently lacking for contacting emergency medicalresponders upon a determination being made that an individual isexperiencing a medical emergency event.

BRIEF SUMMARY

Embodiments of the present technology relate to computer-implementedmethods, systems, and electronic devices for collecting data related tokinetic actions of an individual and for determining the existence of amedical emergency event based upon such kinetic actions.

In a first aspect, a computer-implemented method for detecting medicalemergency events may be provided. The method may include, via one ormore processors, data sensors, and/or transceivers: (1) obtaining sensordata indicative of kinetic actions of a user; (2) analyzing the sensordata to associate the sensor data with a one or more kinetic actions ofthe user; (3) comparing the one or more kinetic actions of the user witha model of kinetic actions to determine whether the one or more kineticactions correspond with the model of kinetic actions, with the model ofkinetic actions being indicative of a medical emergency event; and/or(4) upon determining that the one or more kinetic actions correspondwith the model of kinetic actions, contacting medical emergencyresponders to request medical emergency services for the user (such asvia wireless communication or data transmission over one or more radiofrequency links or digital communication channels). The method mayinclude additional, fewer, or alternative actions, including thosediscussed elsewhere herein, and may be implemented via one or more localor remote processors, and/or via computer-executable instructions storedon non-transitory computer-readable media or medium.

In another aspect, a computer-implemented method for detecting medicalemergency events may be provided. The method may include, via one ormore processors, data sensors, and/or transceivers: (1) obtaining sensordata indicative of kinetic actions of a user; (2) analyzing the sensordata to associate the sensor data with one or more kinetic actions ofthe user; (3) comparing the one or more kinetic actions of the user witha sequential-action model of kinetic actions to determine whether theone or more kinetic actions correspond with the sequential-action model,with the sequential-action model being indicative of a medical emergencyevent; and/or (4) upon determining that the one or more kinetic actionscorrespond with the sequential-action model, contacting medicalemergency responders to request medical emergency services for the user.The method may include additional, fewer, or alternative actions,including those discussed elsewhere herein, and may be implemented viaone or more local or remote processors, and/or via computer-executableinstructions stored on non-transitory computer-readable media or medium.

In another aspect, a computer-implemented method for detecting medicalemergency events may be provided. The method may include, via one ormore processors, data sensors, and/or transceivers: (1) obtaining sensordata indicative of kinetic actions of a user; (2) analyzing the sensordata to associate the sensor data with a kinetic action of the user; (3)comparing the kinetic action of the user with a single-action model ofkinetic actions to determine whether the kinetic action corresponds withthe single-action model, with the single-action model being indicativeof a medical emergency event; and/or (4) upon determining that thekinetic action corresponds with the single-action model, contactingmedical emergency responders to request medical emergency services forthe user. The method may include additional, fewer, or alternativeactions, including those discussed elsewhere herein, and may beimplemented via one or more local or remote processors, and/or viacomputer-executable instructions stored on non-transitorycomputer-readable media or medium.

In another aspect, a mobile electronic device for detecting medicalemergency events may be provided. The mobile electronic device mayinclude one or more processing elements, transceivers, data sensors,and/or memory elements. The memory elements may include a programconfigured to instruct the processing elements to: (1) obtain sensordata indicative of one or more kinetic actions of the user; (2) analyzethe sensor data to associate the sensor data with one or more kineticactions of the user; (3) compare the kinetic actions of the user with amodel of kinetic actions to determine whether the kinetic actionscorresponds with the model of kinetic actions, with the model beingindicative of a medical emergency event; and/or (4) upon determiningthat the kinetic actions correspond with the model of kinetic actions,contact medical emergency responders to request medical emergencyservices for the user. The mobile electronic device may includeadditional, fewer, or alternate components and/or functionality,including that discussed elsewhere herein.

In yet another aspect, non-transitory computer-readable medium with aprogram stored thereon for detecting medical emergency events may beprovided. The program may instruct a processing element to perform thefollowing: (1) obtain sensor data indicative of kinetic actions of auser; (2) analyze the sensor data to associate the sensor data with aone or more kinetic actions of the user; (3) compare the one or morekinetic actions of the user with a model of kinetic actions to determinewhether the one or more kinetic actions correspond with the model ofkinetic actions, with the model being indicative of a medical emergencyevent; and/or (4) upon determining that the one or more kinetic actionscorrespond with the model of kinetic actions, contact medical emergencyresponders to request medical emergency services for the user. Theprogram stored on the computer-readable medium may instruct theprocessing element to perform additional, fewer, or alternative actions,including those discussed elsewhere herein.

Advantages of these and other embodiments will become more apparent tothose skilled in the art from the following description of the exemplaryembodiments which have been shown and described by way of illustration.As will be realized, the present embodiments described herein may becapable of other and different embodiments, and their details arecapable of modification in various respects. Accordingly, the drawingsand description are to be regarded as illustrative in nature and not asrestrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

The Figures described below depict various aspects ofcomputer-implemented methods, systems comprising computer-readablemedia, and electronic devices disclosed therein. It should be understoodthat each Figure depicts an embodiment of a particular aspect of thedisclosed methods, media, and devices, and that each of the Figures isintended to accord with a possible embodiment thereof. Further, whereverpossible, the following description refers to the reference numeralsincluded in the following Figures, in which features depicted inmultiple Figures are designated with consistent reference numerals. Thepresent embodiments are not limited to the precise arrangements andinstrumentalities shown in the Figures.

FIG. 1 illustrates various components of an exemplary mobile electronicdevice shown in block schematic form;

FIG. 2 illustrates various components of an exemplary system fordetecting medical emergency events shown in block schematic form;

FIG. 3 illustrates various components of an exemplary service providercomputer shown in block schematic form;

FIG. 4 illustrates an exemplary computer-implemented method of detectingmedical emergency events in accordance with aspects of the presentembodiments; and

FIG. 5 illustrates an additional exemplary computer-implemented methodof detecting medical emergency events in accordance with aspects of thepresent embodiments.

The Figures depict exemplary embodiments for purposes of illustrationonly. One skilled in the art will readily recognize from the followingdiscussion that alternative embodiments of the systems and methodsillustrated herein may be employed without departing from the principlesof the invention described herein.

DETAILED DESCRIPTION

The present embodiments may relate to, inter alia, computing devices,software applications, systems, and methods for collecting data relatedto kinetic actions of individuals and for determining, based upon suchkinetic actions, whether the individuals are experiencing medicalemergency events. Embodiments of the computing device and/or system,through hardware operation, execution of the software application and/orcomputer program, implementation of the method, or combinations thereof,may be utilized as follows. The computing device of an individual, suchas in the form of a mobile electronic device, may collect sensor datafrom one or more data sensors of the mobile electronic device. Such datamay be indicative of kinetic actions made and/or experienced by theindividual. Based upon such kinetic actions, embodiments may determinethat the individual is experiencing a medical emergency event. In suchcase, embodiments may automatically contact emergency medical respondersto request emergency medical services for the individual, even if theindividual is unable to independently make such a request.

Presently, an individual that experiences a medical emergency event mayhave no method of contacting medical emergency responders for purposesof receiving emergency medical services. As used herein, the termMedical Emergency Event (“ME Event”) may be used to mean an acuteillness or injury that poses an imminent risk to an individual's life orlong-term health. Examples of such ME Events may include: myocardialinfarction (i.e., heart attack), stroke, diabetic episode, drugoverdose, anaphylactic shock, epileptic seizure, accident (e.g., a fallfrom significant height, a vehicle/machine accident, etc.), or the like.Often, such ME Events may cause the individual to lose consciousness orto otherwise be incapacitated. As such, the individual may be unable tocontact emergency medical responders, e.g., emergency medicaltechnicians, paramedics, nurses, doctors, etc. (collectively “EMResponders”) to obtain necessary emergency medical services or treatment(“EM Services”). Given the severity of such ME Events, the individualmay have no more than five to six minutes upon the onset of the ME Eventto contact EM Responders before the individual dies or the individual'slong-term health is significantly compromised.

Certain embodiments of the present invention provide for the detectionof an ME Event experienced by an individual and, in response, for thecontacting of EM Responders, such that the individual can obtainrequisite EM Services in sufficient time to reduce the likelihood ofdeath and/or permanent injury that may otherwise result from the MEEvent. In more detail, embodiments of the present invention may beconfigured to collect, in real-time, sensor data from data sensors of anindividual's mobile electronic device. As used herein, the term “sensordata” is used to mean the data representing position, orientation,direction, displacement, velocity, and/or acceleration of theindividual's mobile electronic device. Such sensor data may be obtainedby various types of data sensors commonly found in mobile electronicdevices, such as accelerometers. Because the individual will generallycarry or otherwise hold his/her mobile electronic device, such sensordata may also be representative of the position, orientation, direction,displacement, velocity, and/or acceleration of the individual's physicalbody.

For instance, the sensor data may be indicative of the orientation ofthe individual's body, e.g. indicative of the individual standingupright, sitting down, lying down, or the like. In addition, the sensordata may be indicative of the direction, heading, and/or velocity atwhich the individual is travelling. Similarly, the sensor data may beindicative of the acceleration the individual is experiencing.Embodiments provide for such sensor data to be continuously collected inreal-time. To ensure that such sensor data can be continuouslycollected, embodiments may include the use of a mobile electronic devicethat is commonly carried or worn by an individual, such as a smartphone,a smartwatch, smart glasses, wearables, smart clothes, or other handheldor wearable computing device.

Upon collecting such sensor data, embodiments of the present inventionprovide for an analysis of the sensor data so as to determine or detectkinetic actions of the individual. As used herein, the term kineticactions may be used to mean physical body movements (or lack thereof),motions, or activities performed by or acted upon the individual.Examples of such kinetic actions include: (i) the individual's physicalbody being oriented in a particular manner (e.g., standing upright,leaning, sitting down, lying down, etc.), (ii) a change in theindividual's orientation, (iii) the individual being immobilized (i.e.,remaining generally motionless), (iii) the individual moving at aparticular speed, (v) the individual falling or collapsing (or, moregenerally, moving under a particular acceleration), (vi) the individualmaking an impact, such as against an object or the ground, (vii) theindividual convulsing (e.g., shaking or trembling), and/or the like.Based upon the kinetic actions, embodiments of the present invention areconfigured to determine or detect whether the individual is experiencingan ME Event.

In some embodiments, the existence of an ME Event may be determined bycomparing an individual's kinetic actions with one or more ME Eventmodels (“Event Model”). Event Models may be comprised of predeterminedpatterns or arrangements of kinetic actions, with such patterns orarrangements being indicative of ME Events. In some embodiments, theEvent Models may include Sequential-Action Models. A Sequential-ActionModel is an Event Model represented by a sequential pattern of kineticactions. For example, in one embodiment, a Sequential-Action Modelindicative of an ME Event may include the following kinetic actions insequential order: an individual falling, the individual making an impact(e.g., with the ground), the individual remaining generally motionless.As such, if an individual experiences such a sequence of kineticactions, embodiments may determine, based upon a comparison between theindividual's kinetic actions with the Sequential-Action Model, that theindividual has experienced an ME Event.

The following is a specific example of detecting an ME Event, in theform of a heart attack, as such an event is experienced by anindividual. The individual may initially be oriented in a standing,upright position. Such an orientation may be detected by the datasensors of the individual's mobile electronic device. From the standingposition, the individual may fall or collapse to the ground. The kineticaction of falling may be determined based upon sensor data obtained bythe accelerometer of the individual's mobile electronic device.Specifically, the accelerometer may sense the acceleration of theindividual as the individual falls to the ground. In some embodiments,such an acceleration may have a magnitude that corresponds with theearth's gravitational acceleration.

In addition to the acceleration, one or more of the sensors of theindividual's mobile electronic device may sense a change in theindividual's orientation during the fall (e.g., a transition from anupright position to a horizontal position, e.g., prone, supine, or thelike). Given the detection of the acceleration and/or the change in theindividual's orientation, embodiments of the present invention maydetermine that the individual has experienced a kinetic action in theform of falling. The kinetic action of falling may, in some embodiments,correspond with an initial kinetic action that is part of aSequential-Action Model indicative of a heart attack-type ME Event.

Continuing with the above heart attack scenario, the kinetic action offalling may be followed by the individual making an impact, and inparticular, making an impact with the ground. The accelerometer of theindividual's mobile electronic device may sense the quick decelerationof the individual's body during such an impact. In some specificembodiments, upon the individual impacting the ground, the individual'sbody may experience a small bounce before coming to rest on the ground.The accelerometer of the individual's mobile electronic device maydetect the bounce as a number of short, alternating changes in theacceleration (i.e., direction and/or magnitude) experienced by theindividual. Given the detection of the deceleration and/or the bounce,embodiments of the present invention may determine that the individualexperienced a kinetic action in the form of an impact with the ground.The kinetic action of the impact may, in some embodiments, correspondwith an intermediate kinetic action that is part of theSequential-Action Model indicative of a heart attack-type ME Event.

Finally, after the individual impacts the ground, the individualexperiencing the heart attack may experience the kinetic action ofremaining generally motionless for a period of time. Such a motionlessstate may correspond to the individual being unconscious, and may besensed by one or more of the data sensors of the individual's mobileelectronic device, such as the accelerometer. The kinetic action ofbeing motionless for a period of time may, in some embodiments,correspond with a final kinetic action that is part of theSequential-Action Model indicative of a heart attack-type ME Event.

Given the sequential pattern of kinetic actions described above,embodiments of the present invention may determine that the individualhas experienced an ME Event, in the form of a heart attack. Inparticular, an analysis of the sensor data collected by the sensors ofthe mobile electronic device may indicate the individual underwent eachof the above-described kinetic actions (i.e., falling, impacting theground, and remaining motionless). Embodiments of the present inventionmay further analyze such kinetic actions by comparing them with one ormore Event Models, including the Sequential-Action Model indicative of aheart attack-type ME Event. Upon determining that the kinetic actionsexperienced by the individual correspond with, or match, theSequential-Action Model indicative of a heart attack attack-type MEEvent, embodiments may determine that the individual was likely to haveexperienced a heart attack-type ME Event. Specifically, as describedabove, the Sequential-Action Model of a heart attack-type ME Event mayinclude the following kinetic actions, in sequential order: (i) a fall,(ii) an impact, and (iii) a motionless period. As such, when the datasensors of the individual's mobile electronic device sense sensor dataindicative of kinetic actions that correspond, in order, with (i) theindividual falling, (ii) the individual impacting the ground, and (iii)the individual remaining motionless for a period of time, embodiments ofthe present invention may determine that the individual has experiencedan ME Event, such as a heart attack.

In response to a determination that the individual has experienced an MEEvent, embodiments pay provide for EM Responders to be contacted so thatthe individual can receive EM Services. In particular, the individual'smobile electronic device may display an alert message on a display ofthe mobile electronic device. The alert message may be in the form of ahealth status question, requesting whether the individual is in need ofEM Services. The mobile electronic device may accept inputs from theindividual in response to the health status question. For instance, theindividual may provide an answer indicating that individual is not inneed of EM Services, in which case no further actions may be taken.Alternatively, if the individual provides an answer indicating that theindividual is need of EM Services, embodiments may provide for EMResponders to be contacted. In some embodiments, the mobile electronicdevice may contact EM Responders by way of a voice communicatingconnection over a cellular network. Alternatively, a text-basedcommunication connection over a data network may be used. The individualmay be able to communicate with the EM Responders over such networks,or, alternatively, an automated message (e.g., automated voice message,text message, email message, or the like), may be sent to the EMResponders over the networks.

However, it should be understood that the individual may only be able toprovide an answer to the health status question if the individual isconscious and/or capable of manipulating a user input of the mobileelectronic device. If the individual is unconscious or is otherwiseunable to manipulate the user input of the mobile electronic device,embodiments of the present invention may, nevertheless, provide for EMResponders to be automatically contacted, even if the individual doesnot provide any response to the health status question. Specifically,for instance, if the individual does not provide an answer to the healthstatus question within a predetermined time period, such as within 5seconds, 10 seconds, 15 seconds, 20 seconds, or more, embodiments mayautomatically contact EM Responders to request EM Services for theindividual. Such contact may be via an automated voice message, a textmessage, an email message, or the like. In addition to requesting EMServices, the mobile electronic device may provide location informationfor the individual, such as may be based upon location determiningelement (as described in more detail below) within the mobile electronicdevice.

The above-described introduction provides an introduction to embodimentsof the present invention, which include computer-implemented methods,systems, and electronic devices for collecting sensor data indicative ofkinetic actions of an individual, and for determining the likelihood ofthe individual experiencing an ME Event based upon such kinetic actions.Upon determining that an individual has likely experienced an ME Event,embodiments may provide for EM Responders to be contacted so as toprovide EM Services to the individual. The contacting of EM Respondersmay be performed automatically, such that even if the individual hasexperienced an ME Event that renders the individual unconscious orotherwise incapacitated, EM Responders can be still be contacted toprovide EM Services to the individual.

Exemplary Embodiments for Collecting Sensor Data and for DeterminingKinetic Actions

The present embodiments described in this patent application and otherpossible embodiments address a computer-centric challenge or problemwith a solution that is necessarily rooted in computer technology andmay relate to computer-implemented methods, systems, and electronicdevices for collecting sensor data related to kinetic actions of a userand for determining the existence of an ME Event based upon such kineticactions.

In more detail, kinetic actions performed by or upon an individual maybe determined by obtaining sensor data from various data sensorsassociated with various types of computing devices. In some embodiments,the computing devices may comprise mobile electronic devices configuredto be carried and/or worn by an individual. For example, in someembodiments, the mobile electronic devices may include smartphones,tablets, smartwatches (or other wearable electronic devices), or thelike. Such mobile electronic devices may include a plurality of datasensors for collecting sensor data related to the mobile electronicdevice and, thus, related to the individual holding or otherwisesupporting the mobile electronic device. For example, the data sensorsincorporated for use in various embodiments of the present invention mayinclude the following: (i) accelerometers for measuring the accelerationof the mobile electronic device, (ii) magnetometers for measuring theorientation and/or directional-heading of the mobile electronic device,(iii) gyroscopes for measuring the orientation and/ordirectional-heading of the mobile electronic device, (iv) locationdetermining elements, such as global positioning system (GPS) elements,for measuring the geolocation of the mobile electronic device, and/or(v) barometers for measuring the atmospheric pressure data and, thus,the height of the mobile electronic device. Although some embodimentsmay incorporate the use of one or more of the above-described datasensors, it should be understood that other data sensors may also beused.

Embodiments may provide for the data sensors of the mobile electronicdevice to be used to collect various types of sensor data related to thekinetic actions of the individual holding or otherwise carrying themobile electronic device. For example, the data sensors may beconfigured to collect the following types of sensor data: (i)orientation data, (ii) elevation or height data, (iii) positionaldisplacement data, (iv) velocity data, and/or (v) acceleration data. Insome embodiments, certain sensor data may be determined from othersensor data. For example, velocity data may be determined by a singleintegration of acceleration data with respect to time. Similarly, apositional displacement may be determined by a double integration ofacceleration data with respect to time. From such sensor data,embodiments provide for the determination of kinetic actions beingperformed by or upon the individual holding or otherwise supporting themobile electronic device. For instance, as was described above, examplesof such kinetic actions include: (i) the individual's physical bodybeing oriented in a particular manner (e.g., standing upright, leaning,sitting down, lying down, etc.), (ii) a change in the individual'sorientation, (iii) the individual being immobilized (i.e., remaininggenerally motionless), (iii) the individual moving at a particularspeed, (v) the individual falling or collapsing (or, more generally,moving under a particular acceleration), (vi) the individual making animpact, such as against an object or the ground, (vii) the individualconvulsing (e.g., shaking or trembling), and/or the like.

In more detail, based upon a change in an individual's orientation, aswell as sensor data related to the individual's velocity andacceleration, embodiments may determine that the individual hasexperienced a kinetic action in the form of falling. A specific exampleof such a kinetic action may include the individual falling orcollapsing to the ground from a standing, upright position. For example,at a starting time, the individual may be standing on the ground in anupright position. The data sensors on the individual's mobile electronicdevice may detect that the mobile electronic device, and thus theindividual, is stationary and not undergoing an acceleration.Furthermore, the sensors of the mobile electronic device may detect thatthe individual is in an upright position based upon the orientation,position, and/or height of the individual holding or otherwisesupporting the mobile electronic device. After the starting time, thesensors may detect that the individual undergoes an acceleration in adownward direction for a period of time (a “period of acceleration”).Furthermore, the data sensors of the mobile electronic device may detectthat during the period of acceleration, the individual's orientation,position, and/or height has changed from the upright position to agenerally horizontal position.

Based upon the individual undergoing the acceleration and/or on thechange in the individual's position/orientation, embodiments maydetermine that the individual underwent a kinetic action in the form offalling (e.g., falling or collapsing to the ground). The determinationof the individual experiencing a kinetic action in the form of fallingmay be further supported by analyzing the characteristics of thecollected sensor data. For example, if the acceleration experienced bythe individual has a magnitude approximately equal to earth'sgravitational acceleration, such as determination may be furtherindicative of the individual experiencing the kinetic action of falling.Although the above description was primarily with reference to fallingfrom an upright, standing position, a kinetic action of falling may alsoinclude falling from significant heights, such as from a ladder or froma building roof.

In addition to the kinetic action of falling, embodiments may alsoinclude a kinetic action in the form of an individual experiencing animpact. An example of such an impact may be the individual impacting theground after falling from an upright standing position. Embodiments mayprovide for such an impact to be determined based upon the data sensorsmeasuring a deceleration of the individual over a short period of time(the “period of deceleration”). In certain instances, the period ofdeceleration associated with an impact may be very short, such as lessthan 2 seconds, less than 1 second, less than 0.5 second, less than 0.25second, or less than 0.1 second. As such, based upon the quickdeceleration, embodiments may determine that the individual hasundergone a kinetic action in the form of an impact. Although the abovedescription referenced an impact with the ground after a fall, thekinetic action of making an impact may also include impacting otherobjects, such as impacting an object while traveling at a high rate ofspeed or being impacted by an object that is travelling at a high rateof speed.

In certain instances, particularly with respect to impacting the ground,the kinetic action of the impact may include, or may be followed by, akinetic action in the form of a “bounce.” In such a bounce, after theindividual initially make an impact with the ground, the direction ofmotion of the individual may transition from moving towards the groundto moving away from the ground. The individual may reach a maximumdistance away from the ground, at which time the direction of motion ofthe individual may again change by moving back towards the ground. Theindividual may again impact the ground (less forcefully) and performadditional cycles of directional changes until the individual settles onthe ground. Each of such directional/acceleration changes may bedetected by the data sensors of the mobile computing device, such that adetermination can be made that the individual has experienced a kineticaction in the form of a bounce.

In addition to the kinetic action of an impact, embodiments may includea kinetic action in the form of remaining generally motionless for aperiod of time (“period of immobility). Such a kinetic action may be dueto the individual being unconscious or otherwise incapacitated.Embodiments may provide for the determination of such a kinetic actionto be based upon the data sensors measuring no or little movement of theindividual over the period of immobility. In some embodiments, theindividual may not be required to be absolutely still to be consideredmotionless. For example, although the individual may be generallyimmobile, the individual may, nevertheless, make small involuntary orvoluntary movements. Such involuntary movements may be due toconvulsions, spasms, tremors, seizures, or the like, whereas voluntarymovements may be due to the individual not being completelyincapacitated but, nevertheless, unable to entirely control his/hermovements. Some embodiments may consider such involuntary or voluntarymovements as not affecting the status of the individual being consideredgenerally motionless if such movements are over a distance of less than10 inches, 8 inches, 5 inches, 4 inches, 3 inches, 2 inches, or 1 inch.Such distances may be measured by the data sensors, such as by theaccelerometer, wherefrom collected acceleration data may be twiceintegrated to determine displacement. Upon the individual remaininggenerally motionless for at least the period of immobility, embodimentsmay determine that the individual has undergone a kinetic action in theform of being motionless.

In addition to the kinetic actions described above (i.e., falling,impacting the ground, remaining motionless), embodiments provide for thedetermination of other kinetic actions performed or experienced by anindividual. For example, embodiments may be configured to determine thatan individual is undergoing convulsive-type movements, which may beindicative of spasms, tremors, seizures, or the like. Suchconvulsive-type movements may be determined from the data sensors of themobile electronic device sensing that the individual is experiencingquick, repetitive changes in acceleration. Such changes in accelerationmay be the result of the individual experiencing repetitive directionalchanges in movement (e.g., a shaking-type movement, a vibrational-typemovement, and/or repetitive back-and-forth movement). Such aconvulsive-type movement may be periodic or non-periodic, and may beassociated with relatively short displacements. For instance, duringeach part of the convulsive-type movements, the individual may bephysically displaced in a particular direction by no more than 1 inch,0.5 inch, 0.25 inch, 0.1 inch, or 0.01 inch, before beginning anotherdisplacement in a different direction.

Embodiments may also provide for the determination of kinetic actions inthe form of the individual travelling at certain velocity. For example,for an individual walking at a normal pace, embodiments may determine,based upon velocity data, that the individual is performing a kineticaction in the form of travelling at a slow rate of speed (or travellingat a low velocity). Examples of slow rates of speed may be between 0.1and 15 miles per hour, 1 and 10 miles per hour, 2 and 6 miles per hour,or 3 and 5 miles per hour. In contrast for an individual driving orriding in a vehicle, embodiments may determine, based upon velocitydata, that the individual is performing the kinetic action of travellingat a high rate of speed (or travelling at a high velocity). Examples ofhigh rates of speed may be between 15 and 1000 miles per hour, 20 and300 miles per hour, 25 and 200 miles per hour, or 30 and 100 miles perhour. As described previously, the velocity of the individual may bedetermined by calculating a single integral of acceleration data overtime.

Exemplary Embodiments for Determining a Medical Emergency Event

Based upon the kinetic actions of the individual, as determined from thesensor data obtained by the mobile electronic device, embodiments may befurther configured to determine whether the individual is likelyexperiencing an ME Event. In some embodiments, the determination of anME Event will be based upon comparing the determined kinetic actionswith models (“Event Models”), which comprise representations of one ormore kinetic actions. For instance, some embodiments may include anEvent Model in the form of a Sequential-Action Model comprising arepresentation of a sequence of kinetic actions. Other embodiments mayinclude an Event Model in the form of a Single-Action Model comprising arepresentation of a single kinetic action.

In more detail, certain embodiments of EM Models may includeSequential-Action Models, with such models comprising a representationof a sequential listing of kinetic actions. For instance, aSequential-Action Model indicative of a heart attack, stroke, drugoverdose, anaphylactic shock, or diabetic episode-type ME Event (a“Collapse sequential model”) may include a representation of thefollowing kinetic actions, in sequential order: (1) an individualfalling, (2) the individual experiencing an impact, and (3) theindividual remaining generally motionless. As such, embodiments cancompare kinetic actions obtained by an individual's mobile electronicdevice with the Collapse sequential model to determine if the individualis experiencing a ME Event in the form of a heart attack, stroke, drugoverdose, anaphylactic shock, or diabetic episode. Specifically, ifembodiments determines that the kinetic actions experienced by theindividual match the sequence of kinetic actions represented by theCollapse sequential model, then embodiments may determine that theindividual is likely experiencing an ME Event, such as a heart attack.For example, if embodiments determine, via the individual's mobileelectronic device, that the individual undergoes the following kineticactions in sequential order: (1) the individual falling, (2) theindividual experiencing an impact, and (3) the individual remaininggenerally motionless, then because such kinetic actions match thesequence of kinetic actions of the Collapse sequential model,embodiments may determine that the individual is likely undergoing an MEEvent, such as a heart attack.

In some embodiments, the Collapse sequential model may include more,less, or different kinetic actions than those described above. Infurther embodiments, the Collapse sequential model may require that, inaddition to the specific sequence of kinetic actions, the kineticactions and/or sensor data have specific values, magnitudes,characteristics and/or time-frames. For example, for the kinetic actionof the individual falling, the Collapse sequential model may requirethat the fall be associated with the individual falling to the groundfrom an upright, standing position. Such a determination may be basedupon various criteria. For example, such a determination may be made byanalyzing the distance the individual travelled while falling. If thedistance travelled by the individual during the period of accelerationcorresponds with the distance the individual would likely travel whenfalling from the upright position to a horizontal position on the ground(e.g., about 2 feet, about 3 feet, about 4 feet, about 5 feet, or thelike), then such analysis may support a determination of the individualexperiencing the kinetic action of falling to the ground. Embodimentsmay provide for such a distance to be calculated by performing a doubleintegration of the acceleration value measured for the individual overthe period of acceleration.

In addition, for the kinetic action of the individual undergoing animpact, the Collapse sequential model may require that the impact beassociated with the individual impacting the ground. Such adetermination may be made based upon multiple criteria, such as theindividual undergoing an impact with a specified impact force indicativeof an impact with the ground after falling from an upright standingposition. In some embodiments, such an impact force may be indicative ofthe individual falling from a particular height, such as from about 2feet, 3 feet, 4 feet, 5 feet, or 6 feet (i.e., indicative of theindividual falling from an upright, standing position to a generallyhorizontal position on the ground). It is generally understood that theforce of an impact corresponds with a change in velocity over an impactperiod (e.g., the period of deceleration). As such, a significant changein velocity may correspond with a significant impact, such as may resultfrom an impact of the individual falling to the ground from an uprightposition. Contrastingly, a relatively low change in velocity maycorrespond to less forceful impact, such as may result from theindividual intentionally sitting down or lying down.

In addition to requiring that the force of the impact and/or the changein velocity of the individual during the impact correspond with a groundimpact, the Collapse sequential model may require that the kineticaction of the impact include a bounce. As was previously described, abounce may consist of a number of directional changes made by theindividual after impacting the ground. In some embodiments, a maximumdistance travelled by the individual in a direction away from the groundduring the bounce may be proportional to the impact force initiallyexperienced by the individual during the impact with the ground.

Finally, for the kinetic action of the individual remaining generallymotionless, the Collapse sequential model may require that theindividual remain generally motionless for a predetermined period oftime. Such predetermined period of time may be for at least 5 seconds,at least 10 seconds, at least 15 seconds, or more. Such a predeterminedperiod of time may be indicative of the individual being unconscious orotherwise incapacitated.

Embodiments may include other Sequential-Action Models in addition tothe Collapse sequential model described above. For instance, embodimentsmay also include a Sequential-Action Model representative of a fall froma significant height (a “SF sequential model”). An individualexperiencing a sequence of kinetic actions that correspond with such SFsequential model may likely be experiencing an ME Event in the form offall, which can result in an acute, severe injury. The SF sequentialmodel may include a representation of the following kinetic actions,which are similar to the Collapse sequential model discussed above,namely: (1) an individual falling, (2) the individual experiencing animpact, and (3) the individual remaining generally motionless.Embodiments may compare kinetic actions obtained by an individual'smobile electronic device with the SF sequential model to determine ifthe individual is experiencing an ME Event due to a fall from asignificant height. Specifically, if embodiments determines that thekinetic actions experienced by the individual match the sequence ofkinetic actions represented by the SF sequential model, then embodimentsmay determine that the individual is likely experiencing an ME Event,such as a significant fall. For example, if embodiments determines, viathe user's mobile electronic device, that the individual undergoes, insequential order, the following kinetic actions: (1) the individualfalling more than a minimum distance, (2) the individual impacting theground, and (3) the individual remaining generally motionless, thenembodiments may determine that the individual is undergoing an ME Eventresulting from a fall from a significant height.

In some embodiments, the SF sequential model may include more, less, ordifferent kinetic actions than those described above. As with theCollapse sequential model, the SF sequential model may require that, inaddition to the specific sequence of kinetic actions, the kineticactions and/or sensor data have specific values, magnitudes,characteristics and/or time-frames. For example, the SF sequential modelmay require that during the kinetic action of falling, the individualfalls a significant minimum distance. Such a significant minimumdistance may be, for instance, at least 5 feet, 10 feet, 15 feet, atleast 20 feet, or more. Such a significant minimum distance maycorrespond to the individual falling from significant height, such asfrom a ladder, from a building roof, or the like. The distance fallen bythe individual may be determined by performing a double integration ofthe acceleration of the individual over the acceleration period.

Additionally, the SF sequential model may require that during thekinetic action of making an impact, the individual must make an impactwith a particular impact force, which is indicative of an impact withthe ground after falling from a significant height (e.g., from at least5 feet, 10 feet, 15 feet, 20 feet, or more). Similarly, the SFsequential model may require that during the kinetic action of making animpact, the individual also undergo a bounce, as was previouslydescribed. In some embodiments, a maximum distance travelled by theindividual in a direction away from the ground during such bounce may beproportional to the impact force of the individual initially impactingthe ground after the fall.

Furthermore, the SF sequential model may require that for the kineticaction of the individual remaining generally motionless, the SFsequential model may require that the individual remain generallymotionless for a predetermined period of time (e.g., at least 5 seconds,10 seconds, 15 seconds, or more). Such a predetermined period of timemay be indicative of the individual being unconscious or otherwiseincapacitated.

Embodiments may also include a Sequential-Action Model representative ofa high-velocity impact (a “HVI sequential model”). The HVI sequentialmodel may be indicative of an individual experiencing an ME Event in theform of an impact after traveling at a high velocity, which may resultin an acute, severe injury. The HVI sequential model may comprise arepresentation of the following kinetic actions, in sequential order:(1) an individual traveling at a high velocity, (2) the individualexperiencing an impact, and (3) the individual remaining generallymotionless. As such, embodiments may compare an individual's kineticactions, as obtained by the individual's mobile electronic device, withthe HVI sequential model to determine if the individual is experiencinga ME Event in the form of a high-velocity impact.

Specifically, if embodiments determines that the kinetic actionsexperienced by the individual match the sequence of kinetic actionsrepresented by the HVI sequential model, then embodiments may determinethat the individual is likely experiencing an ME Event in the form of ahigh-velocity impact. For example, if embodiments determines that theindividual undergoes, in sequential order, the following kineticactions: (1) the individual travelling at a high velocity, (2) theindividual making a high-velocity impact, and (3) the individualremaining generally motionless, then embodiments may determine that theindividual is undergoing am ME Event in the form of a high-velocityimpact.

In some embodiments, the HVI sequential model may include more, less, ordifferent kinetic actions than those described above. As with thepreviously-discussed Sequential-Action Models, the HVI sequential modelmay require that, in addition to the specific sequence of kineticactions, the kinetic actions and/or sensor data have specific values,magnitudes, characteristics and/or time-frames. In some embodiments, theHVI sequential model may require that during the kinetic action oftraveling at a high velocity includes the individual travelling at leastat a minimum speed. Such minimum speed may be, for instance, at least 10miles per hour, 15 miles per hour, 20 miles per hour, 25 miles per hour,or more. Similarly, the HVI sequential model may require that thekinetic action of the individual making the high-velocity impact makesuch an impact with at least a minimum impact force. Furthermore, forthe kinetic action of the individual remaining generally motionless, theHVI sequential model may require that the individual remain generallymotionless for a period of time (e.g., at least 5 seconds, at least 10seconds, etc.). Such a period of time may be indicative of theindividual being unconscious or otherwise incapacitated.

In addition to the sequential models, such as those described above,embodiments may be used to determine the existence of an ME Event basedupon a Single-Action Model. An example of a Single-Action Model mayinclude a convulsive model. Such a convulsive model may be indicative ofan individual undergoing an ME Event in the form of epileptic seizures,spasms, tremors, or the like. The convulsive model may comprise arepresentation of a kinetic action in the form of quick, convulsive-typemovements of the individual's body for a period of time (the “convulsiveperiod”). In some embodiments, the convulsive model may require that theconvulsive period be at least 5 seconds, at least 10 seconds, or more.Additionally, in some embodiments, the convulsive model may require thatthe convulsive-type movements have specific frequencies and/or may causespecific, repetitive positional displacements of the individual's body.For example, in some embodiments, the positional displacements of theindividual's body during a convulsive-type movement may be less thanabout 1 inch, less than 0.5 inch, less than 0.25 inch, less than 0.1inch, or less than 0.01 inch. Embodiments can compare kinetic actionsobtained by an individual's mobile electronic device with the convulsivemodel to determine if the individual is experiencing an ME Event due anepileptic seizure, spasm, tremor, or the like.

Specifically, if embodiments determines that the kinetic actionexperienced by the individual matches the kinetic actions represented bythe convulsive model, then embodiments may determine that the individualis likely experiencing an ME Event in the form of an epileptic seizure,spasm, tremor, or the like. For example, if embodiments determines, viathe user's mobile electronic device, that the individual undergoes akinetic action in the form of convulsive-type movements for a particularperiod of time (i.e., the convulsive period), then embodiments maydetermine that the individual is undergoing an ME Event resulting froman epileptic seizure, spasm, tremor, or the like.

Another example of a Single-Action model may include an isolated-impactmodel. Such an isolated-impact model may be indicative of an individualundergoing an ME Event in the form of an isolated impact, which mayresult in an acute severe injury. An example of such an isolated impactmay include a non-moving impact resulting from the individual being hitas a pedestrian by a large and/or fast moving object, such as a vehicle.The isolated-impact model may require that the individual experience animpact that satisfies at least a minimum impact force. Such a minimumimpact force may be indicative of the individual being impacted by alarge and/or fast-moving object, such as a vehicle. In some embodiments,the isolated-impact model may further require that the individual not bemoving, or be moving relatively slowly, in the moments immediately priorto the impact. Such slow or non-movement may be indicative of theindividual being impacted by a moving object, as opposed to theindividual making an impact with another object while the individual istravelling at a high speed (i.e., as would be involved in ahigh-velocity impact). Embodiments can compare kinetic actions obtainedby an individual's mobile electronic device with the isolated-impactmodel to determine if the individual is experiencing an ME Event due toan isolated impact.

Specifically, if embodiments determines that the kinetic actionexperienced by the individual matches the kinetic action represented bythe isolated-impact model, then embodiments may determine that theindividual is likely experiencing an ME Event in the form of an isolatedimpact. For example, if embodiments determines, via the user's mobileelectronic device, that the individual undergoes a kinetic action in theform of a quick change in acceleration that includes a high impactforce, then embodiments may determine that the individual is undergoingan ME Event resulting from a sudden impact.

Embodiments provide for the ME Models to be predetermined and pre-set.However, in some embodiments, the ME Models may be continually developedand refined as sensor data and kinetic actions are obtained byindividual users of the present invention. For instance, variousembodiments may utilize machine learning programs or techniques torecognize ME Events from kinetic actions. The programs may include curvefitting, regression model builders, convolutional or deep learningneural networks, pattern recognition techniques, or the like. Moreover,automated data analysis and machine learning environments may, incertain embodiments, assist in ME Event analysis and detection. Forinstance, for heart attack-type ME Events, embodiments may continuallyrefine the value or magnitude of representative kinetic actions that door do not indicate the likelihood of a heart attack-type ME Event.

As a particular example, some embodiments of the Collapse sequentialmodel require that the impact force of the kinetic action of theindividual impacting the ground satisfy a minimum magnitude before adetermination can be made that the individual's kinetic actions matchthe Collapse sequential model, so as to indicate that the individual islikely undergoing a heart attack-type ME Event. As more individuals useembodiments of the present invention, and as more sensor data andkinetic actions are analyzed from such individuals, the minimummagnitude of the impact force indicative of an individual impacting theground during a heart attack-type ME Event can be continually refined.As such, as embodiments of the present invention continues to collectsensor data related to kinetic actions of individuals, the Event Modelscan be more accurately specified.

Furthermore, as will be discussed in more detail below, in someembodiments, individuals may be required to provide individual profiledata, which may include medical information. The medical information mayinclude information relevant to the individual's previous medicalhistory, such as history of heart disease, high-blood pressure, druguse, allergies, diabetes, epilepsy, and the like. In some embodiments,the determination of whether an individual is undergoing an ME Event maybe based, at least in part, on the individual's medical information. Forinstance, some embodiments may specify that even if an individual'skinetic actions match an ME model, the determination as to whether theindividual is experiencing an ME Event may further require that theindividual has a requisite medial history. As an example, an individualmay undergo kinetic actions that match the Collapse sequential model.However, certain embodiments may not make a determination that theindividual has experienced an ME Event unless the individual has amedical history that includes heart disease, high-blood pressure, or thelike.

Exemplary Embodiments for Contacting Emergency Services

Upon a determination that an individual is likely undergoing an MEEvent, embodiments may provide for EM Responders to be contacted so asto provide the individual with EM Services. In more detail, upon an MEEvent even being detected, embodiments provide for an alert message(e.g., a push notification, email, text, or other alert message) to beprovided to the individual, with such alert message indicating thedetection of an ME Event and, further, inquiring as to whether theindividual requires EM Services. In some embodiments, the alert messagemay be provided via a graphic display of the individual's mobileelectronic device. For example, the alert message may be provided in theform of a graphical dialogue box that includes a health status questionin the form of: “A medical emergency has been detected—Do you needimmediate medical assistance?” The alert message may include one or morepredetermined answer interfaces, which may be presented asgraphically-selectable buttons, check boxes, or the like (collectively“answer interfaces”). For instance, the alert message may include a“yes” answer interface, which is indicative of the individual answeringthat he/she is in need of immediate EM Services, and a “no” answerinterface, which is indicative of the individual answering that he/sheis not in need of EM Services.

Upon the individual selecting the “yes” answer indicator in response tothe health status question, the mobile electronic device may connectwith EM Responders (or to dispatchers of the EM Responders) to requestEM Services to be provided to the individual. In some embodiments, theconnection may be over a voice communications network, such as acellular communications network to which the individual's mobileelectronic device may be connected. Via the voice communicationsnetwork, the individual may personally communicate with the EMResponders, or the mobile electronic device may provide an automatedrequest message to the EM Responders indicating that the individual hasexperienced a ME Event and is need of immediate EM Services. In otherembodiments, the request message may be sent by other methods of datacommunications, such as by SMS text messaging, email messaging, or thelike.

In certain embodiments in which an automated request message is sent tothe EM Responders, the automated request message may include informationrelevant to the individual experiencing the ME Event. For example, insome embodiments, the request message may include the individual's name,health history information, and current location. To facilitate theprovision of such information to the EM Responders, in some embodiments,the individual may be required to upload individual profile data to theindividual's mobile electronic device and/or to other computing devicesthat may be included within certain embodiments of the presentinvention.

Such individual profile data may include personal information, medicalinformation, and/or contact information. The personal information mayinclude information such as the individual's name, age, sex, height,weight, and the like. The medical information may include informationrelevant to the individual's previous medical history, such as historyof heart disease, high-blood pressure, drug use, allergies, diabetes,epilepsy, etc. Such information may be provided so that the EMResponders can provide appropriate EM Services to the individual. Thecontact information may be the individual's home address, work address,telephone number, next of kin, or the like.

In some embodiments, contact information provided by the individual maybe used by the EM Responders as the location to which to travel to forpurposes of providing EM Services to the individual. Alternatively, insome embodiments, the individual's mobile electronic device may providethe individual's current geolocation, which is obtained from thelocation determining element (i.e., GPS) of the mobile electronicdevice. As such, EM Responders will have the requisite geolocationinformation necessary to travel to the individual's location so as toprovide EM Services to the individual.

Should the individual select the “no” answer indicator in response tothe health status question or push notification, the mobile electronicdevice may perform no further actions. Specifically, because theindividual indicated that the individual was not experiencing a ME Eventand was not in need of medical attention, EM Responders may not becontacted.

As a further alternative, should the individual fail to provide ananswer to the health status question within a predefined period of time,such as within 5 seconds, 10 seconds, 15 seconds, within 20 seconds, orsome other timer period, the mobile electronic device may automaticallyconnect with EM Responders to request EM Services for the individual.Specifically, the individual failing to provide an answer to the alertmessage may be indicative of the individual being unconscious orotherwise incapacitated, such that the individual is not capable ofproviding an answer to the alert message. As such, embodiments may beconfigured to automatically connect with EM Responders to request EMServices for the individual, as was previously described.

Specific embodiments of the technology will now be described inconnection with the attached drawing figures. The embodiments areintended to describe aspects of the invention in sufficient detail toenable those skilled in the art to practice the invention. Otherembodiments may be utilized and changes may be made without departingfrom the scope of the present invention. The following detaileddescription is, therefore, not to be taken in a limiting sense. Thescope of the present invention is defined only by the appended claims,along with the full scope of equivalents to which such claims areentitled.

Exemplary Mobile Electronic Device

FIG. 1 depicts an embodiment of an exemplary mobile electronic device 10for use in determining whether an individual is experiencing an MEEvent. The mobile electronic device 10 may be embodied as a smartphone,a tablet computer, a laptop computer, a phablet, smart glasses, asmartwatch, wearable electronics, or the like, and may, as illustratedin FIG. 2, broadly comprise a display 12, a user interface 14, alocation determining element 16, one or more data sensors 18, a memoryelement 20, and a processing element 22. The mobile electronic device 10may also include a communication element 24 configured as one or moretransceivers that utilize radio frequency (RF) communication, such ascellular, WiFi, Bluetooth™, or the like, to communicate with otherdevices, systems, or networks.

The display 12 may include video devices of the following types: plasma,light-emitting diode (LED), organic LED (OLED), Light Emitting Polymer(LEP) or Polymer LED (PLED), liquid crystal display (LCD), thin filmtransistor (TFT) LCD, LED side-lit or back-lit LCD, heads-up displays(HUDs), or the like, or combinations thereof. The display 12 may includea screen on which the information is presented, with the screenpossessing a square or a rectangular aspect ratio that may be viewed ineither a landscape or a portrait mode. In various embodiments, thedisplay 12 may also include a touch screen occupying the entire screenor a portion thereof so that the display 12 functions as part of theuser interface 14. The touch screen may allow the user to interact withthe mobile electronic device 10 by physically touching, swiping, orgesturing on areas of the screen.

The user interface 14 generally allows the user to utilize inputs andoutputs to interact with the mobile electronic device 10. Inputs mayinclude buttons, pushbuttons, knobs, jog dials, shuttle dials,directional pads, multidirectional buttons, switches, keypads,keyboards, mice, joysticks, microphones, or the like, or combinationsthereof. Outputs may include audio speakers, lights, dials, meters,printers, or the like, or combinations thereof. With the user interface14, the user may be able to control the features and operation of thedisplay 12. For example, the user may be able to zoom in and out on thedisplay 12 using either virtual onscreen buttons or actual pushbuttons.In addition, the user may be able to pan the image on the display 12either by touching and swiping the screen of the display 12 or by usingmultidirectional buttons or dials.

The location determining element 16 generally determines a currentgeolocation of the mobile electronic device 10 and may receive andprocess radio frequency (RF) signals from a global navigation satellitesystem (GNSS) such as the global positioning system (GPS) primarily usedin the United States, the GLONASS system primarily used in the SovietUnion, or the Galileo system primarily used in Europe. The locationdetermining element 16 may accompany or include an antenna to assist inreceiving the satellite signals. The antenna may be a patch antenna, alinear antenna, or any other type of antenna that may be used withlocation or navigation devices. The location determining element 16 mayinclude satellite navigation receivers, processors, controllers, othercomputing devices, or combinations thereof, and memory. The locationdetermining element 16 may process a signal, referred to herein as a“location signal”, from one or more satellites that includes data fromwhich geographic information such as the current geolocation is derived.The current geolocation may include coordinates, such as the latitudeand longitude, of the current location of the mobile electronic device10. The location determining element 16 may communicate the currentgeolocation to the processing element 22, the memory element 20, orboth.

Although embodiments of the location determining element 16 may includea satellite navigation receiver, it will be appreciated that otherlocation-determining technology may be used. For example, cellulartowers or any customized transmitting radio frequency towers may be usedinstead of satellites may be used to determine the location of themobile electronic device 10 by receiving data from at least threetransmitting locations and then performing basic triangulationcalculations to determine the relative position of the device withrespect to the transmitting locations. With such a configuration, anystandard geometric triangulation algorithm may be used to determine thelocation of the mobile electronic device. The location determiningelement 16 may also include or be coupled with a pedometer,accelerometer, compass, or other dead-reckoning components which allowit to determine the location of the mobile computing device 10. Thelocation determining element 16 may determine the current geographiclocation through a communications network, such as by using Assisted GPS(A-GPS), or from another electronic device. The location determiningelement 16 may even receive location data directly from a user.

The data sensors 18 generally detect the position, orientation, speed,and acceleration of the mobile computing device 10 and, thus, theindividual holding or otherwise supporting the mobile electronic device.The data sensors 18 may be selected from one or more of the followingsensors: (i) accelerometers, (ii) magnetometers, (iii) gyroscopes,and/or (iv) barometers. The accelerometer may be used to measure linearacceleration relative to a frame of reference, and thus, can be used todetect motion of the mobile electronic device 10 as well as to detect anangle or orientation of the mobile electronic device 10 relative to thehorizon or ground. By calculating an integral of a measured accelerationwith respect to time, embodiments may use data obtained by theaccelerometer to measure a velocity of the mobile electronic device 10.Similarly, by calculating a double integral of a measured accelerationwith respect to time, embodiments may use data obtained by theaccelerometer to measure a displacement distance of the mobileelectronic device.

The magnetometer may be used as a compass to determine a direction ofmagnetic north and bearings of the mobile electronic device 10 relativeto magnetic north. The gyroscope may be used to detect both vertical andhorizontal orientation of the mobile electronic device 10, and togetherwith the accelerometer and magnetometer may be used to obtain veryaccurate information about the orientation of the mobile computingdevice 10. The barometer may be used to detect both a pressure of theatmosphere in which the mobile electronic device 10 is positioned. Assuch, the barometer may be used to measure altitudes and heights, aswell as to measure changes in altitudes and heights. In some additionalembodiments, the location determining element 16 may be included as adata sensors 18. Although some embodiments may incorporate the use ofone or more of the above-described sensors for the data sensors 18 ofthe mobile electronic device 10, it should be understood that othersensors may also be used.

The memory element 20 may include one or more electronic hardware datastorage components such as read-only memory (ROM), programmable ROM,erasable programmable ROM, random-access memory (RAM) such as static RAM(SRAM) or dynamic RAM (DRAM), cache memory, hard disks, floppy disks,optical disks, flash memory, thumb drives, universal serial bus (USB)drives, or the like, or combinations thereof. In some embodiments, thememory element 20 may be embedded in, or packaged in the same packageas, the processing element 22. The memory element 20 may include, or mayconstitute, a “computer-readable medium.” The memory element 20 maystore the instructions, code, code segments, software, firmware,programs, applications, apps, services, daemons, or the like that areexecuted by the processing element 22.

The processing element 22 may include one or more electronic hardwarecomponents such as processors, microprocessors (single-core andmulti-core), microcontrollers, digital signal processors (DSPs),field-programmable gate arrays (FPGAs), analog and/or digitalapplication-specific integrated circuits (ASICs), or the like, orcombinations thereof. The processing element 22 may generally execute,process, or run instructions, code, code segments, software, firmware,programs, applications, apps, processes, services, daemons, or the like.The processing element 22 may also include hardware components such asfinite-state machines, sequential and combinational logic, and otherelectronic circuits that may perform the functions necessary for theoperation of the current invention. The processing element 22 may be incommunication with the other electronic components through serial orparallel links that include address busses, data busses, control lines,and the like.

The various processes, functions, and features of embodiments of thepresent invention discussed herein may be performed by the processingelement 22 of the mobile computing device 10 carrying out instructionsof a computer program, software, firmware, or combinations thereofstored on the memory element 20. In some embodiments, the computerprogram may be in the form of a mobile “app.”

For instance, the processing element 22 may be programmed or configuredto perform the following functions. The processing element 22 may beconfigured to obtain sensor data from one or more of the data sensors 18of the mobile electronic device 10. The processing element 22 may beconfigured to analyze the sensor data to determine kinetic actions ofthe individual carrying or otherwise holding the mobile electronicdevice 10. The processing element 22 may also be configured to comparethe kinetic actions with one or more Event Models to determine if theindividual is likely undergoing an ME Event. Furthermore, the processingelement 22 may be configured to transmit communications via thecommunication element 24 to EM Responders to request EM Services for theindividual.

Exemplary Service Provider Computer and Network

FIG. 2 depicts exemplary embodiments of a system, which may be utilizedfor detecting ME Events. The system may include a network 27 and aservice provider computer 28, in addition to mobile electronic device10. In such embodiments, the various processes, functions, and featuresof embodiments of the present invention discussed herein may beperformed in part by the service provider 28 and/or in part (orentirely) by the mobile computing device 10. For example, the mobilecomputing device 10 may be configured to obtain sensor data from thedata sensors 18 and to provide such sensor data to the service providercomputer 28 via the network 27. The service provider computer 28 may,thus, be configured to execute instructions of a computer program,software, firmware, or combinations thereof to analyze the sensor datato determine kinetic actions and to detect ME Events.

In some alternative embodiments, the mobile computing device 10 may beconfigured to perform all processes, functions, and features describedherein by carrying out the instructions of a computer program and/orsoftware that is downloaded from the service provider computer 28 viathe network 27. Such computer program and/or software may be updatedfrom time to time by the mobile electronic device 10 downloading updatesand/or new versions for the computer program and/or software from theservice provider computer 28. For example, the service provider computer28 may store updates of the Event Models, such as may be determined bycurve fitting, regression model builders, convolutional or deep learningneural networks, pattern recognition techniques, or the like. Suchupdated Event Models may be periodically provided to the mobileelectronic device 10 over the network 27, such that the mobileelectronic device 10 can compare a user's kinetic actions with the mostcurrent Event Models.

The network 27 may generally allow communication between the mobileelectronic device 10 and the service provider computer 28, such as viawireless communication or data transmission over one or more radio linksor wireless communication channels. The network 27 may also providecommunication between the mobile electronic device 10 and/or the serviceprovider computer 28 and EM Responders (and/or the dispatchers for EMResponders). The network 27 may include local area networks, metro areanetworks, wide area networks, cloud networks, the Internet, cellularnetworks, plain old telephone service (POTS) networks, and the like, orcombinations thereof. The network 27 may be wired, wireless, orcombinations thereof and may include components such as modems,gateways, switches, routers, hubs, access points, repeaters, towers, andthe like. The mobile electronic device 10 generally connects to thenetwork 27 wirelessly, such as radio frequency (RF) communication usingwireless standards such as cellular 2G, 3G, or 4G, Institute ofElectrical and Electronics Engineers (IEEE) 802.11 standards such asWiFi, IEEE 802.16 standards such as WiMAX, Bluetooth®, or combinationsthereof.

The service provider computer 28 generally retains electronic data andmay respond to requests to retrieve data as well as to store data. Insome embodiments, the service provider computer 28 may also performcertain of the processes, functions, and features described herein withrespect to detecting ME Events by executing portions, or the entirety,of the computer program and/or software of embodiments of the presentinvention. The service provider computer 28 may be embodied by apersonal computer such as a desktop workstation and/or laptop computer,and/or by application servers, database servers, file servers, gamingservers, mail servers, print servers, web servers, or the like, orcombinations thereof. Furthermore, the service provider computer 28 mayinclude a plurality of servers, virtual servers, or combinationsthereof. The service provider computer 28 may be configured to includeor execute software such as file storage applications, databaseapplications, email or messaging applications, web server applications,or the like, in addition to and/or in conjunction with the computerprogram and/or software described elsewhere herein.

The service provider computer 28 may include a communication element 30,a processing element 34, and a memory element 38. The communicationelement 30 generally allows communication with external systems ordevices. The communication element 30 may include signal or datatransmitting and receiving circuits, such as antennas, transceivers,amplifiers, filters, mixers, oscillators, digital signal processors(DSPs), and the like. The communication element 30 may establishcommunication wirelessly by utilizing RF signals and/or data that complywith communication standards such as cellular 2G, 3G, or 4G, IEEE 802.11standard such as WiFi, IEEE 802.16 standard such as WiMAX, Bluetooth™,or combinations thereof. Alternatively, or in addition, thecommunication element 30 may establish communication through connectorsor couplers that receive metal conductor wires or cables which arecompatible with networking technologies such as ethernet. In certainembodiments, the communication element 30 may also couple with opticalfiber cables. The communication element 30 may be in communication withor electronically coupled to memory element 38 and/or processing element34.

The memory element 38 may include data storage components such asread-only memory (ROM), programmable ROM, erasable programmable ROM,random-access memory (RAM) such as static RAM (SRAM) or dynamic RAM(DRAM), cache memory, hard disks, floppy disks, optical disks, flashmemory, thumb drives, USB ports, or the like, or combinations thereof.The memory element 38 may include, or may constitute, a“computer-readable medium”. The memory element 38 may store theinstructions, code, code segments, software, firmware, programs,applications, apps, services, daemons, or the like that are executed bythe processing element 34. The memory element 38 may also storesettings, data, documents, sound files, photographs, movies, images,databases, and the like.

The processing element 34 may include processors, microprocessors,microcontrollers, DSPs, field-programmable gate arrays (FPGAs), analogand/or digital application-specific integrated circuits (ASICs), or thelike, or combinations thereof. The processing element 34 may generallyexecute, process, or run instructions, code, code segments, software,firmware, programs, applications, apps, processes, services, daemons, orthe like. The processing element 34 may also include hardwarecomponents, such as finite-state machines, sequential and combinationallogic, and other electronic circuits that may perform the functionsnecessary for the operation of embodiments of the current inventiveconcept. The processing element 34 may be in communication with theother electronic components through serial or parallel links thatinclude address busses, data busses, control lines, and the like.

Exemplary Computer-Implemented Method

FIG. 4 depicts an exemplary computer-implemented method 100 fordetecting ME Events. The steps may be performed in the order shown inFIG. 4, or they may be performed in a different order. Furthermore, somesteps may be performed concurrently as opposed to sequentially. Inaddition, some steps may be optional. The steps of thecomputer-implemented method may be performed by a processing element ofthe mobile electronic device, by a processing element of the serviceprovider computer, and/or one or more local or remote processors.

A first step 102 of the method 100 may include obtaining sensor datafrom one or more data sensors of a mobile computing device, with suchsensor data indicative of kinetic actions of a user. For example, insome embodiments, the one or more data sensors may comprise anaccelerometer configured to obtain sensor data in the form ofacceleration data of the user. A next step 104 of the method 100 mayinclude analyzing the sensor data to determine one or more kineticactions of the user. Examples of such kinetic actions may include, forinstance, (1) the user falling to the ground, (2) the user impacting theground, and/or (3) the user remaining generally motionless. A next step106 of the method 100 may include comparing the kinetic actions of theuser with a Sequential-Action Model of kinetic actions indicative of anME Event. A Sequential-Action Model may representative of particularsequence of kinetic actions. Examples of such ME Events include heartattacks, strokes, seizures, falls, accidents, or the like. If thekinetic actions of the user are determined to correspond with theSequential-Action Model, a next step 108 may include contactingemergency services to request medical assistance for the user. The flowof FIG. 4 may include additional, less, or alternate actions, includingthose discussed elsewhere herein.

Another Exemplary Computer-Implemented Method

FIG. 5 depicts another exemplary computer-implemented method 200 fordetecting medical emergency events. The steps may be performed in theorder shown in FIG. 5, or they may be performed in a different order.Furthermore, some steps may be performed concurrently as opposed tosequentially. In addition, some steps may be optional. The steps of thecomputer-implemented method may be performed by a processing element ofthe mobile electronic device, by a processing element of the serviceprovider computer, and/or one or more local or remote processors.

A first step 202 of the method 200 may include obtaining sensor datafrom one or more data sensors of a mobile computing device, with suchdata indicative of kinetic actions of a user. For example, in someembodiments, the one or more sensors may comprise an accelerometerconfigured to obtain sensor data in the form of acceleration data of theuser. A next step 204 of the method 200 may include analyzing the datato determine a kinetic action of the user. Examples of such kineticactions may include, for instance (1) the user undergoing a convulsion,or (2) the user experiencing an isolated impact. A next step 206 of themethod 200 may include comparing the kinetic action of the user with aSingle-Action Model of a kinetic action indicative of an ME Event. ASingle-Action Model may be representative of particular kinetic actions.Examples of such ME Events include seizures, a sudden impact with avehicle, or the like. If the kinetic action of the user is determined tocorrespond with the Single-Action Model, a next step 208 of the method200 may include contacting EM Responders to request EM Services for theuser. The flow of FIG. 5 may include additional, less, or alternateactions, including those discussed elsewhere herein.

Exemplary Computer Systems

In one aspect, a computer system configured to detect medical emergencyevents may be provided. The computer system may include one or moreprocessors, servers, transceivers, and/or sensors configured to: (1)obtain or receive sensor data generated from one or more sensorsindicative of kinetic actions of a user (such as via wirelesscommunication or data transmission over one or more radio frequencylinks or digital communication channels); (2) analyze the sensor data toassociate the sensor data with one or more kinetic actions of the user;(3) compare the one or more kinetic actions of the user with a model ofkinetic actions to determine whether the one or more kinetic actionscorrespond with the model of kinetic actions, wherein the model ofkinetic actions is indicative of a medical emergency event; and/or (4)upon determining that the one or more kinetic actions correspond withthe model of kinetic actions, contact, via wireless communication ordata transmission over one or more radio links or digital communicationchannels, medical emergency responders to request medical emergencyservices for the user.

In another aspect, a computer system configured to detect medicalemergency events may be provided. The computer system may include one ormore processors, servers, sensors, and/or transceivers configured to:(1) obtain or receive sensor data generated from one or more sensorsindicative of kinetic actions of a user (such as via wirelesscommunication or data transmission over one or more radio frequencylinks or digital communication channels); (2) analyze the sensor data toassociate the sensor data with one or more kinetic actions of the user;(3) compare the one or more kinetic actions of the user with asequential-action model of kinetic actions to determine whether the oneor more kinetic actions correspond with the sequential-action model,wherein the sequential-action model is indicative of a medical emergencyevent; and/or (4) upon determining that the one or more kinetic actionscorrespond with the sequential-action model, contacting, via wirelesscommunication or data transmission over one or more radio links ordigital communication channels, medical emergency responders to requestmedical emergency services for the user.

In another aspect, a computer system configured to detect medicalemergency events may be provided. The computer system may include one ormore processors, sensors, transceivers, and/or servers configured to:(1) obtain or receive sensor data generated by one or more sensorsindicative of kinetic actions of a user (such as via wirelesscommunication or data transmission over one or more radio links ordigital communication channels); (2) analyze the sensor data toassociate the sensor data with a kinetic action of the user; (3) comparethe kinetic action of the user with a single-action model of kineticactions to determine whether the kinetic action corresponds with thesingle-action model, wherein the single-action model is indicative of amedical emergency event; and/or (4) upon determining that the kineticaction corresponds with the single-action model, contact, via wirelesscommunication or data transmission over one or more radio links ordigital communication channels, medical emergency responders to requestmedical emergency services for the user.

The foregoing computer systems may include additional, less, oralternate functionality, including that discussed elsewhere herein.

Additional Considerations

In this description, references to “one embodiment”, “an embodiment”, or“embodiments” mean that the feature or features being referred to areincluded in at least one embodiment of the technology. Separatereferences to “one embodiment”, “an embodiment”, or “embodiments” inthis description do not necessarily refer to the same embodiment and arealso not mutually exclusive unless so stated and/or except as will bereadily apparent to those skilled in the art from the description. Forexample, a feature, structure, act, etc. described in one embodiment mayalso be included in other embodiments, but is not necessarily included.Thus, the current technology may include a variety of combinationsand/or integrations of the embodiments described herein.

Although the present application sets forth a detailed description ofnumerous different embodiments, it should be understood that the legalscope of the description is defined by the words of the claims set forthat the end of this patent and equivalents. The detailed description isto be construed as exemplary only and does not describe every possibleembodiment since describing every possible embodiment would beimpractical. Numerous alternative embodiments may be implemented, usingeither current technology or technology developed after the filing dateof this patent, which would still fall within the scope of the claims.

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Certain embodiments are described herein as including logic or a numberof routines, subroutines, applications, or instructions. These mayconstitute either software (e.g., code embodied on a machine-readablemedium or in a transmission signal) or hardware. In hardware, theroutines, etc., are tangible units capable of performing certainoperations and may be configured or arranged in a certain manner. Inexample embodiments, one or more computer systems (e.g., a standalone,client or server computer system) or one or more hardware modules of acomputer system (e.g., a processor or a group of processors) may beconfigured by software (e.g., an application or application portion) ascomputer hardware that operates to perform certain operations asdescribed herein.

In various embodiments, computer hardware, such as a processing element,may be implemented as special purpose or as general purpose. Forexample, the processing element may comprise dedicated circuitry orlogic that is permanently configured, such as an application-specificintegrated circuit (ASIC), or indefinitely configured, such as an FPGA,to perform certain operations. The processing element may also compriseprogrammable logic or circuitry (e.g., as encompassed within ageneral-purpose processor or other programmable processor) that istemporarily configured by software to perform certain operations. Itwill be appreciated that the decision to implement the processingelement as special purpose, in dedicated and permanently configuredcircuitry, or as general purpose (e.g., configured by software) may bedriven by cost and time considerations.

Accordingly, the term “processing element” or equivalents should beunderstood to encompass a tangible entity, be that an entity that isphysically constructed, permanently configured (e.g., hardwired), ortemporarily configured (e.g., programmed) to operate in a certain manneror to perform certain operations described herein. Consideringembodiments in which the processing element is temporarily configured(e.g., programmed), each of the processing elements need not beconfigured or instantiated at any one instance in time. For example,where the processing element comprises a general-purpose processorconfigured using software, the general-purpose processor may beconfigured as respective different processing elements at differenttimes. Software may accordingly configure the processing element toconstitute a particular hardware configuration at one instance of timeand to constitute a different hardware configuration at a differentinstance of time.

Computer hardware components, such as communication elements, memoryelements, processing elements, and the like, may provide information to,and receive information from, other computer hardware components.Accordingly, the described computer hardware components may be regardedas being communicatively coupled. Where multiple of such computerhardware components exist contemporaneously, communications may beachieved through signal transmission (e.g., over appropriate circuitsand buses) that connect the computer hardware components. In embodimentsin which multiple computer hardware components are configured orinstantiated at different times, communications between such computerhardware components may be achieved, for example, through the storageand retrieval of information in memory structures to which the multiplecomputer hardware components have access. For example, one computerhardware component may perform an operation and store the output of thatoperation in a memory device to which it is communicatively coupled. Afurther computer hardware component may then, at a later time, accessthe memory device to retrieve and process the stored output. Computerhardware components may also initiate communications with input oroutput devices, and may operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processing elements thatare temporarily configured (e.g., by software) or permanently configuredto perform the relevant operations. Whether temporarily or permanentlyconfigured, such processing elements may constitute processingelement-implemented modules that operate to perform one or moreoperations or functions. The modules referred to herein may, in someexample embodiments, comprise processing element-implemented modules.

Similarly, the methods or routines described herein may be at leastpartially processing element-implemented. For example, at least some ofthe operations of a method may be performed by one or more processingelements or processing element-implemented hardware modules. Theperformance of certain of the operations may be distributed among theone or more processing elements, not only residing within a singlemachine, but deployed across a number of machines. In some exampleembodiments, the processing elements may be located in a single location(e.g., within a home environment, an office environment or as a serverfarm), while in other embodiments the processing elements may bedistributed across a number of locations.

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“presenting,” “displaying,” or the like may refer to actions orprocesses of a machine (e.g., a computer with a processing element andother computer hardware components) that manipulates or transforms datarepresented as physical (e.g., electronic, magnetic, or optical)quantities within one or more memories (e.g., volatile memory,non-volatile memory, or a combination thereof), registers, or othermachine components that receive, store, transmit, or displayinformation.

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus. Further, unless expressly stated to the contrary,“or” refers to an inclusive or and not to an exclusive or.

The patent claims at the end of this patent application are not intendedto be construed under 35 U.S.C. § 112(f) unless traditionalmeans-plus-function language is expressly recited, such as “means for”or “step for” language being explicitly recited in the claim(s).

Although the invention has been described with reference to theembodiments illustrated in the attached drawing figures, it is notedthat equivalents may be employed and substitutions made herein withoutdeparting from the scope of the invention as recited in the claims.

Having thus described various embodiments of the invention, what isclaimed as new and desired to be protected by Letters Patent includesthe following:
 1. A computer-implemented method for detecting medicalemergency events, the computer-implemented method comprising: analyzingsensor data, via one or more processing elements, to associate thesensor data with one or more kinetic actions of the user, wherein thesensor data is analyzed to determine if the user has experienced akinetic action in the form of a bounce, wherein the kinetic action ofthe bounce is indicated by one or more accelerometers measuring aplurality of quick, alternating changes in acceleration; comparing, viathe one or more processing elements, the one or more kinetic actions ofthe user with a model of kinetic actions to determine whether the one ormore kinetic actions correspond with the model of kinetic actions,wherein the model of kinetic actions is indicative of a medicalemergency event; and upon determining that the one or more kineticactions correspond with the model of kinetic actions, contacting, viaone or more transceivers, medical emergency responders to requestmedical emergency services for the user.
 2. The computer-implementedmethod of claim 1, wherein the sensor data comprises orientation data.3. The computer-implemented method of claim 1, wherein the sensor datacomprises geolocation data.
 4. The computer-implemented method of claim1, wherein the data sensors, in addition to one or more accelerometers,are further selected from one or more of the following: magnetometers,gyroscopes, global positioning system elements, and barometers.
 5. Thecomputer-implemented method of claim 1, wherein the one or moreprocessors comprises a processor of a mobile electronic device.
 6. Thecomputer-implemented method of claim 5, wherein the mobile electronicdevice is selected from one of the following: a smartphone, a tablet, aphablet, smart glasses, and a smartwatch.
 7. The computer-implementedmethod of claim 5, wherein the mobile electronic device comprises asmartphone.
 8. The computer-implemented method of claim 1, wherein thekinetic actions of the user comprise one or more of the following: theuser falling to the ground, the user impacting the ground, and the userremaining motionless.
 9. The computer-implemented method of claim 1,wherein the model of kinetic actions comprises a sequential-actionmodel.
 10. The computer-implemented method of claim 9, wherein thesequential-action model is representative of a sequence of kineticactions.
 11. The computer-implemented method of claim 10, wherein thesequence of kinetic actions represented by the sequential-action modelcomprises the following: the user falling to the ground, the userimpacting the ground, and the user remaining motionless.
 12. Thecomputer-implemented method of claim 11, wherein the kinetic action offalling to the ground represented by the sequential-action modelincludes falling under an acceleration having a magnitude thatcorresponds to earth's gravitational acceleration.
 13. Thecomputer-implemented method of claim 11, wherein the kinetic action ofimpacting the ground represented by the sequential-action model includesimpacting the ground with a specified impact force.
 14. Thecomputer-implemented method of claim 11, wherein the kinetic action ofremaining motionless represented by the sequential-action model includesremaining motionless for at least a predetermined period of time. 15.The computer-implemented method of claim 14, wherein the predeterminedperiod of time is 5 seconds.
 16. The computer-implemented method ofclaim 1, wherein the medical emergency event is selected from one ormore of the following: a heart attack, a stroke, and a high-velocityimpact.
 17. The computer-implemented method of claim 9, wherein the oneor more kinetic actions of the user correspond with thesequential-action model if the one or more kinetic actions of the usersequentially match the kinetic actions represented by thesequential-action model.
 18. The computer-implemented method of claim 1,wherein the kinetic actions of the user comprise the user falling to theground.
 19. The computer-implemented method of claim 1, wherein thekinetic actions of the user comprise the user remaining motionless. 20.A system for detecting medical emergency events, said system comprising:one or more data sensors configured to obtain sensor data indicative ofkinetic actions of a user; and a computing device comprising one or moreprocessing elements and one or more transceivers, wherein said computingdevice is configured to— obtain, from the one or more data sensors,sensor data indicative of kinetic actions of the user, analyze thesensor data, via the one or more processing elements, to associate thesensor data with one or more kinetic actions of the user, wherein thesensor data is analyzed to determine if the user has experienced akinetic action in the form of a bounce, wherein the kinetic action ofthe bounce is indicated by one or more accelerometers measuring aplurality of quick, alternating changes in acceleration, compare, viathe one or more processing elements, the one or more kinetic actions ofthe user with a model of kinetic actions to determine whether the one ormore kinetic actions correspond with the model of kinetic actions,wherein the model of kinetic actions is indicative of a medicalemergency event, and upon determining that the one or more kineticactions correspond with the model of kinetic actions, contacting, viathe one or more transceivers, medical emergency responders to requestmedical emergency services for the user.